CN109900300B - A combination navigation integrity monitoring system for unmanned aerial vehicle - Google Patents

A combination navigation integrity monitoring system for unmanned aerial vehicle Download PDF

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CN109900300B
CN109900300B CN201910236625.0A CN201910236625A CN109900300B CN 109900300 B CN109900300 B CN 109900300B CN 201910236625 A CN201910236625 A CN 201910236625A CN 109900300 B CN109900300 B CN 109900300B
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CN109900300A (en
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王志鹏
朱衍波
刘伟
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Beihang University
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/01—Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/13—Receivers
    • G01S19/20—Integrity monitoring, fault detection or fault isolation of space segment
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/10—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration
    • G01C21/12—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning
    • G01C21/16—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation
    • G01C21/165—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation combined with non-inertial navigation instruments
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G5/00—Traffic control systems for aircraft, e.g. air-traffic control [ATC]
    • G08G5/0047—Navigation or guidance aids for a single aircraft
    • G08G5/006—Navigation or guidance aids for a single aircraft in accordance with predefined flight zones, e.g. to avoid prohibited zones
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G5/00—Traffic control systems for aircraft, e.g. air-traffic control [ATC]
    • G08G5/0047—Navigation or guidance aids for a single aircraft
    • G08G5/0069—Navigation or guidance aids for a single aircraft specially adapted for an unmanned aircraft

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Abstract

The invention provides a combined navigation integrity monitoring system for an unmanned aerial vehicle, which comprises: the inertia measurement device is used for providing zero offset values of the inertia measurement devices of different grades for the processor; a receiver for receiving global satellite navigation signals and providing integrity risks of a global satellite navigation system to a processor; a processor for calculating a horizontal protection level of the integrated navigation and a vertical protection level of the integrated navigation; the method comprises the steps of setting a horizontal warning limit and a vertical warning limit, comparing the calculated horizontal protection level and the calculated vertical protection level with the corresponding horizontal warning limit and the corresponding vertical warning limit respectively, and monitoring the integrity of the unmanned aerial vehicle.

Description

A combination navigation integrity monitoring system for unmanned aerial vehicle
Technical Field
The invention relates to the technical field of aviation navigation, in particular to a combined navigation integrity monitoring system for an unmanned aerial vehicle.
Background
With the increasing application of Unmanned Aerial Vehicles (UAVs) in the civil field, many convenience is brought to work and life of people, such as agricultural plant protection Unmanned Aerial vehicles, Aerial photography Unmanned Aerial vehicles and the like, but many potential safety hazards are brought, such as frequent occurrence of 'black flight' events, flying in crowded places and airports and the like, and many troubles are brought to production and life of the society. How to effectively realize safe flight of the UAV in the controlled airspace is a practical problem in the current application in the civil field of UAVs. The UAV safety control system has the advantages that safety measures for ensuring the UAV to fly in a specific area are taken, operation safety is ensured, safe and effective flying in a specific airspace is realized, on one hand, the UAV can be limited in a region where a no-fly area is arranged to realize no-fly, on the other hand, the UAV can be efficiently controlled, interference on normal production and life of people is avoided, and production and life safety of people is endangered.
The combined Navigation technology of a Global Navigation Satellite System (GNSS) and an Inertial Navigation System (INS) can provide real-time, stable and accurate position information for the UAV. The GNSS/INS combined navigation system can provide horizontal navigation service and vertical navigation service. The integrity of the INS system is guaranteed by the traditional method which is realized by redundancy on hardware, however, in the civil field, the limitation on the hardware cost is generally considered, so the integrity of the INS system is guaranteed by the hardware redundancy method, and obviously, the method does not meet the requirement of practical application. The Integrity of the GNSS system is generally guaranteed by using a Receiver Autonomous Integrity Monitoring (RAIM) technology.
Therefore, in order to overcome the limitation that the integrity of the INS system is realized by adopting redundancy on hardware in the prior art, a combined navigation integrity monitoring method for the unmanned aerial vehicle needs to be used without hardware redundancy and reduce the cost.
Disclosure of Invention
The invention aims to provide an integrated navigation integrity monitoring system for an unmanned aerial vehicle, which comprises:
the inertia measurement device is used for providing zero offset values of the inertia measurement devices of different grades for the processor;
a receiver for receiving global satellite navigation signals and providing integrity risks of a global satellite navigation system to a processor;
a processor for calculating a horizontal protection level of the integrated navigation and a vertical protection level of the integrated navigation, wherein the horizontal protection level of the integrated navigation is calculated by the following method:
HPL＝max{HPLGNSS,fault,HPLIMU,fault,HPLIMU,Nominalin which, HPLGNSS,faultFor the level of protection under the assumption of global satellite navigation system failure, HPLIMU,faultFor the level of protection under the assumption of inertial navigation faults, HPLIMU,NominalA horizontal protection level under the nominal assumption of inertial navigation;
the vertical protection level of the combined navigation is calculated by the following method:
VPL＝max{VPLGNSS,fault,VPLIMU,fault,VPLIMU,Nominalwherein, VPLGNSS,faultVPL, a vertical protection level under the assumption of global satellite navigation system failureIMU,faultFor the vertical protection level under the assumption of inertial navigation faults, VPLIMU,NominalThe vertical protection level under the nominal assumption of inertial navigation;
the processor further executes the following instructions: and setting a horizontal warning limit by taking the transverse size of the unmanned aerial vehicle as a reference, setting a vertical warning limit by taking the longitudinal size of the unmanned aerial vehicle as a reference, comparing the calculated horizontal protection level of the combined navigation with the horizontal warning limit, and comparing the calculated vertical protection level of the combined navigation with the vertical warning limit to monitor the unmanned aerial vehicle.
Preferably, the level of protection HPL under the nominal assumption of inertial navigation is saidIMU,NominalCalculated by the following method:
HPLIMU,Nominal＝Kmd,INS,HσIMU,std,h，
wherein σIMU,std,hFor the standard deviation of the performance parameter of the inertial measurement unit in the horizontal direction, Kmd,INS,HSetting a missing detection coefficient in the horizontal direction for the inertial navigation nominal value;
missing detection coefficient K in horizontal direction under nominal assumption of inertial navigationmd,INS,HObtained by the following method:
Kmd,INS,H＝Q-1(λIMU,std,hPHMI,H,Nominal)，
wherein Q is a cumulative distribution function of zero-mean Gaussian distribution, λIMU,std,hThe weight ratio of the integrity risk errors in the horizontal direction under the nominal assumption of inertial navigation satisfies 0 & ltlambdaIMU,std,h＜1，PHMI,H,NominalNominally assuming an assigned integrity risk in the horizontal direction for inertial navigation;
standard deviation sigma of performance parameter of the inertia measurement device in horizontal directionIMU,std,hObtained by the following method:
Figure BDA0002008383790000031
wherein σIMU,std,NIs the standard deviation, sigma, in the north east sky coordinate systemIMU,std,EIs the east standard deviation in the northeast coordinate system.
Preferably, the HPL is a horizontal protection class under the assumption of inertial navigation faultIMU,faultCalculated by the following method:
Figure BDA0002008383790000032
wherein σIMU,fault,hFor fault deviations in the horizontal direction under the assumption of inertial navigation faults, Kmd,INS-fault,HSetting a missing detection coefficient in the horizontal direction for inertial navigation fault, Kk,iIs the kalman filter gain at the current sampling instant i,
Figure BDA0002008383790000033
is the process noise offset correction at the current sampling instant i,ω,ithe noise covariance matrix input for the current time instant i,
Figure BDA0002008383790000034
k is a process noise vector of the current time i, the state of an extended Kalman filtering equation in the integrated navigation is k, and N is 1, 2 and …;
missing detection coefficient K in horizontal direction under inertial navigation fault assumptionmd,INS-fault,HObtained by the following method:
Kmd,INS-fault,H＝Q-1(λIMU,fault,hPHMI,H,INS)，
wherein Q is a cumulative distribution function of zero-mean Gaussian distribution, λIMU,fault,hThe weight ratio of integrity risk errors in the horizontal direction is assumed for inertial navigation faults and satisfies the condition that lambda is more than 0IMU,fault,h＜1，PHMI,H,INSAssuming an integrity risk assigned in the horizontal direction for inertial navigation faults;
fault deviation σ in horizontal direction under assumption of inertial navigation faultIMU,fault,hObtained by the following method:
Figure BDA0002008383790000035
wherein σIMU,fault,NIs the deviation of north fault in the coordinate system of northeastIMU,fault,EIs the east fault deviation in the northeast coordinate system.
Preferably, the HPL is a level of protection under the assumption of global navigation satellite system failureGNSS,faultCalculated by the following method:
HPLGNSS,fault＝μmax,h+Kffmd,Hσxk,h，
wherein,
Figure BDA0002008383790000041
is the mean position deviation muk,iComponent μ in the horizontal directionk,h,iThe arithmetic mean correction amount of (1), Kffmd,HSetting a missing detection coefficient in the horizontal direction, sigma, for a global navigation system faultxk,hA fault deviation in the horizontal direction under the assumption of a global navigation system fault,
missing detection coefficient K in horizontal direction under fault assumption of global navigation systemffmd,HObtained by the following method:
Kffmd,H＝Q-1(PHMI,H,GNSS/2)，
wherein Q is a cumulative distribution function of zero-mean Gaussian distribution, PHMI,H,GNSSGlobal navigation system failures assume integrity risks assigned in the horizontal direction.
Preferably, the vertical protection level VPL under the nominal assumption of inertial navigationIMU,NominalThe inertial navigation is calculated under the nominal assumption by the following method:
VPLIMU,Nominal＝Kmd,INS,VσIMU,std,v，
wherein σIMU,std,vFor the standard deviation of the performance parameter of the inertial measurement unit in the vertical direction, Kmd,INS,VNominal assumed sag for inertial navigationA straight direction miss detection coefficient;
the missing detection coefficient K in the vertical direction under the nominal assumption of inertial navigationmd,INS,VObtained by the following method:
Kmd,INS,V＝Q-1(1-λIMU,std,vPHMI,V,Nominal)，
wherein Q is a cumulative distribution function of zero-mean Gaussian distribution, λIMU,std,vThe weight ratio of integrity risk errors in the vertical direction under the nominal assumption of inertial navigation satisfies 0 < lambdaIMU,std,v＜1，PHMI,V,NominalNominally assuming an assigned integrity risk in the down-vertical direction for inertial navigation;
the standard deviation sigma of the performance parameter of the inertial measurement unit in the vertical directionIMU,std,vObtained by the following method:
σIMU,std,v＝σIMU,std,U，
wherein σIMU,std,vIs the standard deviation of the north east sky coordinate system.
Preferably, the vertical protection level VPL under the assumption of inertial navigation faultIMU,faultCalculated by the following method:
Figure BDA0002008383790000042
wherein σIMU,fault,vFor fault deviations in the vertical direction under the assumption of inertial navigation faults, Kmd,INS-fault,VSetting a vertical missing detection coefficient for inertial navigation fault, Kk,iIs the kalman filter gain at the current sampling instant i,
Figure BDA0002008383790000054
is the process noise offset correction at the current sampling instant i,ω,ithe noise covariance matrix input for the current time instant i,
Figure BDA0002008383790000055
k is the process noise vector of the current time i and k is the extension in the integrated navigationThe state of the kalman filter equation, N ═ 1, 2, …;
vertical direction missing detection coefficient K under inertial navigation fault assumptionmd,INS-fault,VObtained by the following method:
Kmd,INS-fault,V＝Q-1(1-λIMU,fault,vPHMI,V,INS)，
wherein Q is a cumulative distribution function of zero-mean Gaussian distribution, λIMU,fault,vThe weight ratio of integrity risk errors in the vertical direction is assumed for inertial navigation faults and satisfies the condition that lambda is more than 0IMU,fault,v＜1，PHMI,V,INSAssuming an assigned integrity risk in the vertical direction for inertial navigation faults;
fault deviation σ in vertical direction under assumption of inertial navigation faultIMU,fault,vObtained by the following method:
σIMU,fault,v＝σIMU,fault,U，
wherein σIMU,fault,UThe north east sky coordinate system is the sky fault deviation.
Preferably, the VPL is a vertical protection level under the assumption of global satellite navigation system failureGNSS,faultCalculated by the following method:
Figure BDA0002008383790000051
wherein,
Figure BDA0002008383790000052
is the mean position deviation muk,iComponent μ in the vertical directionk,v,iThe arithmetic mean correction amount of (1), Kffmd,VA vertical missing detection coefficient is assumed for the global navigation system fault,
Figure BDA0002008383790000053
a fault deviation in the vertical direction under the assumption of a global navigation system fault,
missing detection coefficient K in horizontal direction under fault assumption of global navigation systemffmd,VBy passingThe method comprises the following steps:
Kffmd,V＝Q-1(1-PHMI,V,GNSS/2)，
wherein Q is a cumulative distribution function of zero-mean Gaussian distribution, PHMI,V,GNSSGlobal navigation system failures assume integrity risks assigned in the vertical direction.
Preferably, 1.1-1.3 times of the transverse size of the unmanned aerial vehicle is set as a first horizontal warning limit, 1.1-1.3 times of the longitudinal size of the unmanned aerial vehicle is set as a first vertical warning limit, so that the space cube enclosed by the first horizontal warning limit and the first vertical warning limit is reduced to the flight trajectory of the unmanned aerial vehicle,
comparing the calculated horizontal protection level of the integrated navigation with the first horizontal warning limit, comparing the vertical protection level of the integrated navigation with the first vertical warning limit,
when the horizontal protection level is higher than the first horizontal warning limit and/or the vertical protection level is higher than the first vertical warning limit, the horizontal protection level of the combined navigation and the vertical protection level of the combined navigation are recalculated so that the horizontal protection level is lower than the first horizontal warning limit and the vertical protection level is lower than the first vertical warning limit.
Preferably, 100-1000 times of the transverse size of the unmanned aerial vehicle is set as a second horizontal warning limit, 100-1000 times of the longitudinal size of the unmanned aerial vehicle is set as a second vertical warning limit, a space cube enclosed by the second horizontal warning limit and the second vertical warning limit forms a flight airspace of the unmanned aerial vehicle,
comparing the calculated horizontal protection level of the integrated navigation with a second horizontal warning limit, comparing the vertical protection level of the integrated navigation with a second vertical warning limit,
when the horizontal protection level is higher than the second horizontal warning limit and/or the vertical protection level is higher than the second vertical warning limit, the horizontal protection level of the combined navigation and the vertical protection level of the combined navigation are recalculated so that the horizontal protection level is lower than the second horizontal warning limit and the vertical protection level is lower than the second vertical warning limit.
According to the integrated navigation integrity monitoring system for the unmanned aerial vehicle, integrity risks are distributed in the horizontal direction and the vertical direction, the integrity risks in the horizontal direction and the vertical direction are divided into a nominal hypothesis, an inertial navigation fault hypothesis and a global navigation fault hypothesis, horizontal protection and vertical protection levels are calculated respectively, the inertial navigation system is realized without hardware redundancy, and the integrated navigation integrity monitoring cost can be reduced.
According to the integrated navigation integrity monitoring system for the unmanned aerial vehicle, hardware redundancy of an Inertial Navigation System (INS) is not needed, so that the navigation cost of the unmanned aerial vehicle is greatly reduced, and interference of redundant information is avoided.
According to the integrated navigation integrity monitoring system for the unmanned aerial vehicle, risks are distributed to a horizontal domain and a vertical domain through integrity risk distribution, and then fault hypotheses of the horizontal domain and the vertical domain are divided into a nominal hypothesis, a global navigation system fault hypothesis and an inertial navigation fault hypothesis, so that the integrity of the system is guaranteed from a system level, and the integrity of each branch is guaranteed from a hardware level.
According to the integrated navigation integrity monitoring system for the unmanned aerial vehicle, planning and tracking of the unmanned aerial vehicle navigation path can be realized only by limiting the horizontal warning limit and the vertical warning limit according to the requirements of practical application. And corresponding horizontal warning limits and vertical warning limits can be set according to the determined specific flight airspace boundary, so that the safe flight of the unmanned aerial vehicle in the control airspace can be realized, and the practical application of corresponding airspace flight prohibition and the like can be derived.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention, as claimed.
Drawings
Further objects, features and advantages of the present invention will become apparent from the following description of embodiments of the invention, with reference to the accompanying drawings, in which:
fig. 1 schematically shows a structural diagram of an integrated navigation integrity monitoring system for a drone according to the present invention.
Fig. 2 shows a schematic diagram of the integrity risk classification of the present invention.
FIG. 3 is a flow chart illustrating the process of calculating the horizontal and vertical protection levels by the processor according to the present invention.
Fig. 4 shows a schematic view of the unmanned aerial vehicle navigation route planning according to an embodiment of the invention.
Fig. 5 shows a schematic view of the unmanned aerial vehicle governing airspace boundary according to another embodiment of the present invention.
Detailed Description
The objects and functions of the present invention and methods for accomplishing the same will be apparent by reference to the exemplary embodiments. However, the present invention is not limited to the exemplary embodiments disclosed below; it can be implemented in different forms. The nature of the description is merely to assist those skilled in the relevant art in a comprehensive understanding of the specific details of the invention.
Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings. In the drawings, the same reference numerals denote the same or similar parts, or the same or similar steps.
In order to solve the problem of high integrated navigation cost caused by the fact that integrated navigation of an unmanned aerial vehicle in the prior art needs to rely on hardware redundancy to realize the limitation of the integrity of an inertial navigation system, the invention provides an integrated navigation integrity monitoring system for the unmanned aerial vehicle, which does not need hardware redundancy and reduces the navigation cost of the unmanned aerial vehicle.
The invention considers the horizontal protection level (Ho) of the navigation information of the unmanned aerial vehicle in the airspace where the unmanned aerial vehicle is positionedrizontal Protection Level, HPL) and Vertical Protection Level (VPL) requirements. Because the integrity of the navigation system of the unmanned aerial vehicle needs to be capable of detecting navigation faults in real time, providing integrity risk information for users and timely making corresponding reactions when faults occur, the integrity risks of the users are distributed to the horizontal direction and the vertical direction, and then the integrity risks P in the horizontal direction and the vertical direction are distributedHMIDividing into three conditions of nominal hypothesis fault, Inertial Navigation (INS) fault and global navigation system (GNSS) fault, and respectively calculating horizontal protection under each fault hypothesisThe maximum values of the corresponding horizontal protection stage (HPL) and the vertical protection stage (VPL) are taken in the same direction at the same time as the horizontal protection stage (HPL) and the vertical protection stage (VPL) at the sampling time, so that the dependence on hardware redundancy is omitted.
As shown in fig. 1, a schematic structural diagram of an integrated navigation integrity monitoring system for a drone according to the present invention is an integrated navigation integrity monitoring system for a drone according to an embodiment of the present invention, including:
an inertial measurement unit 102 for providing different levels of zero offset values of the inertial measurement unit to the processor 103.
A receiver 101 for receiving signals of global satellite navigation 200 and providing integrity risk of the global satellite navigation system to the processor 103. The Integrity risk of the global navigation satellite system is implemented using Receiver Autonomous Integrity Monitoring (RAIM) technology.
And the processor 103 is used for calculating the horizontal protection level of the combined navigation and the vertical protection level of the combined navigation. The process of the present invention for calculating the horizontal guard level of the combined navigation and the vertical guard level of the combined navigation by the processor 103 is described in detail below.
For the purpose of making the present invention clearer, the integrity risk classification of the present invention is given in the embodiment before the calculation of the horizontal protection level of the integrated navigation and the vertical protection level of the integrated navigation, as shown in fig. 2, a schematic diagram of the integrity risk classification of the present invention, an integrity risk PHMI,TotalDivided into horizontal integrity risk PHMI,HorizontalAnd risk of vertical integrity PHMI,VerticalClassifying the risk of horizontal integrity and the risk of vertical integrity according to a nominal hypothesis, an inertial navigation fault hypothesis and a global navigation system fault hypothesis, namely:
integrity risk P assigned in horizontal direction under nominal assumption of inertial navigationHMI,H,Nominal。
Integrity risk P assigned in horizontal direction under assumption of inertial navigation faultHMI,H,INS。
Global navigation systemIntegrity risk P assigned in horizontal direction under fault assumptionHMI,H,GNSS。
Assigned integrity risk P in the vertical direction under the nominal assumption of inertial navigationHMI,V,Nominal。
Inertial navigation fault hypothesis integrity risk P assigned in the down-vertical directionHMI,V,INS。
Global navigation system fault hypothesis integrity risk P assigned in a downward directionHMI,V,GNSS。
Through the above integrity risk classification, the horizontal protection level of the integrated navigation and the vertical protection level of the integrated navigation are calculated, as shown in fig. 3, the processor of the present invention processes a flow chart for calculating the horizontal protection level and the vertical protection level.
Computing a level of protection for integrated navigation
The level of protection (HPL) for the combined navigation is calculated by:
HPL＝max{HPLGNSS,fault,HPLIMU,fault,HPLIMU,Nominalin which, HPLGNSS,faultFor the level of protection under the assumption of global satellite navigation system failure, HPLIMU,faultFor the level of protection under the assumption of inertial navigation faults, HPLIMU,NominalThe level of protection is nominally assumed for inertial navigation.
According to an embodiment of the invention, the HPL is a horizontal protection level under nominal assumption of inertial navigationIMU,NominalCalculated by the following method:
HPLIMU,Nominal＝Kmd,INS,HσIMU,std,h，
wherein σIMU,std,hFor the standard deviation of the performance parameter of the inertial measurement unit in the horizontal direction, Kmd,INS,HAnd (4) setting a missing detection coefficient in the horizontal direction for the inertial navigation.
Standard deviation σ of performance parameters of an inertial measurement unit in the horizontal direction under nominal assumption of no failureIMU,std,hDetermined by the north and east deviations of the inertial measurement unit, i.e. by the inertial measurement unit in the north-east coordinate systemThe deviation of the piece in both the north and east directions is determined.
According to an embodiment of the invention, the standard deviation σ of the performance parameter of the inertial measurement unit in the horizontal directionIMU,std,hObtained by the following method:
Figure BDA0002008383790000091
wherein σIMU,std,NIs the standard deviation, sigma, in the north east sky coordinate systemIMU,std,EIs the east standard deviation in the northeast coordinate system.
Standard deviation σ in north direction under northeast sky coordinate systemIMU,std,NAnd east standard deviation σ in the northeast coordinate systemIMU,std,EThe zero offset values for different grades of inertial measurement units are provided according to the zero offset values for different grades of inertial measurement units, as shown in table 1. According to the actual situation of the deviation of the inertial measurement device, the standard deviation in the horizontal direction is described by using the standard deviation in the north direction and the standard deviation in the east direction together, and the integrity in the horizontal direction is guaranteed from the original parameters of inertial navigation.
TABLE 1 zero offset values for different levels of inertia measurement devices
Inertial Measurement Unit (IMU) rating Accelerometer zero offset (m/s)-2) Gyroscope zero offset (rad/s)-1)
Air level 3×10-4～10-3 5×10-8
Tactical level 0.01～0.1 5×10-6～5×10-4
Consumption level Greater than 0.03 Greater than 5 x 10-4
Missing detection coefficient K in horizontal direction under inertial navigation nominal assumptionmd,INS,HObtained by the following method:
Kmd,INS,H＝Q-1(λIMU,std,hPHMI,H,Nominal)，
wherein Q is a cumulative distribution function of zero-mean Gaussian distribution, λIMU,std,hThe weight ratio of the integrity risk errors in the horizontal direction under the nominal assumption of inertial navigation satisfies 0 & ltlambdaIMU,std,hIf the weight ratio of the integrity risk error in the horizontal direction is less than 1, the higher the precision of the inertial measurement device is, the closer the weight ratio of the integrity risk error in the horizontal direction is to 0 under the nominal assumption of inertial navigation, and otherwise, the lower the precision of the inertial measurement device is, the closer the weight ratio of the integrity risk error in the horizontal direction is to 1 under the nominal assumption of inertial navigation.
According to table 1, zero offset values for different classes of inertial measurement units, in some embodiments, the inertial navigation nominal assumes a horizontal integrity risk error weight ratio of 1/12, 5/12, 9/12, respectively, when using aviation-, tactical-, and consumer-class inertial measurement units, respectively.
PHMI,H,NominalThe assigned integrity risk in the horizontal direction is nominally assumed for inertial navigation.
Under the assumption of inertial navigation fault, establishing an extended Kalman filtering state Equation (EKF) of the integrated navigation:
Figure BDA0002008383790000101
Figure BDA0002008383790000102
measurement information in extended Kalman Filter State equation
Figure BDA0002008383790000103
Derived from pseudorange observations of the global navigation system,
Figure BDA0002008383790000104
is the output vector of the inertial measurement unit,
Figure BDA0002008383790000105
is a vector of a prediction of the state,
Figure BDA0002008383790000106
is to update the state vector of the state vector,kandωrespectively an input covariance matrix and a noise covariance matrix,
Figure BDA0002008383790000107
is the process noise vector, phikFor a state transfer matrix, KkIs the Kalman filter gain, HkIs the system transmission matrix.
According to the embodiment of the invention, under the condition that the inertial measurement unit introduces a fault hypothesis, the arithmetic mean of a filter gain term and a process noise deviation correction quantity in an extended Kalman filter state equation is introduced to calculate the HPL under the condition that the inertial navigation fault hypothesis is generatedIMU,fault。
In particular, the HPL of the horizontal protection class under the assumption of inertial navigation faultsIMU,faultThe following method is used for calculation:
Figure BDA0002008383790000111
wherein σIMU,fault,hIs an inertia guideFault deviation in horizontal direction under the assumption of flight fault, Kmd,INS-fault,HSetting a missing detection coefficient in the horizontal direction for inertial navigation fault, Kk,iIs the kalman filter gain at the current sampling instant i,
Figure BDA0002008383790000112
is the process noise offset correction at the current sampling instant i,ω,ithe noise covariance matrix input for the current time instant i,
Figure BDA0002008383790000113
and k is the state of the extended kalman filter equation in the integrated navigation, and N is 1, 2, …, which is the process noise vector at the current time i.
Missing detection coefficient K in horizontal direction under inertial navigation fault assumptionmd,INS-fault,HObtained by the following method:
Kmd,INS-fault,H＝Q-1(λIMU,fault,hPHMI,H,INS)，
wherein Q is a cumulative distribution function of zero-mean Gaussian distribution, λIMU,fault,hThe weight ratio of integrity risk errors in the horizontal direction is assumed for inertial navigation faults and satisfies the condition that lambda is more than 0IMU,fault,h＜1，PHMI,H,INSAn assigned integrity risk in the horizontal direction is assumed for inertial navigation faults.
Fault deviation σ in horizontal direction under inertial navigation fault assumption in case of fault assumption introduced by inertial measurement unitIMU,fault,hThe fault deviation of the inertial measurement unit in the north direction and the east direction is determined, namely the fault deviation of the inertial measurement unit in the north-east coordinate system in the north direction and the east direction is determined.
Fault deviation σ in horizontal direction under assumption of inertial navigation faultIMU,fault,hObtained by the following method:
Figure BDA0002008383790000114
wherein σIMU,fault,NIs the deviation of north fault in the coordinate system of northeastIMU,fault,EIs the east fault deviation in the northeast coordinate system. Northbound fault deviation sigma under northeast coordinate systemIMU,fault,NAnd east fault deviation sigma in northeast coordinate systemIMU,fault,EFrom the residual error in the above extended Kalman Filter State equation
Figure BDA0002008383790000115
The standard difference component in the north and east directions is determined.
According to an embodiment of the invention, a HPL of horizontal protection class under the assumption of global navigation satellite system failureGNSS,faultCalculated by the following method:
Figure BDA0002008383790000121
wherein,
Figure BDA0002008383790000122
is the mean position deviation muk,iComponent μ in the horizontal directionk,h,iThe arithmetic mean correction amount of (1), Kffmd,HA missing detection coefficient in the horizontal direction is assumed for the global navigation system fault,
Figure BDA0002008383790000123
fault deviation in the horizontal direction under the assumption of global navigation system fault.
In the above process, the average position deviation mu is obtained by using a Receiver Autonomous Integrity Monitoring (RAIM) methodk,iComponent μ in the horizontal directionk,h,iThe arithmetic mean correction amount of (1). Obtaining fault deviation sigma in horizontal direction under global navigation system fault assumption through extended Kalman filter state Equation (EKF)xk,h。
Missing detection coefficient K in horizontal direction under fault assumption of global navigation systemffmd,HObtained by the following method:
Kffmd,H＝Q-1(PHMI,H,GNSS/2)，
wherein Q is a cumulative distribution function of zero-mean Gaussian distribution, PHMI,H,GNSSGlobal navigation system failures assume integrity risks assigned in the horizontal direction.
Vertical protection level for computing combined navigation
The Vertical Protection Level (VPL) of the combined navigation is calculated by the following method:
VPL＝max{VPLGNSS,fault,VPLIMU,fault,VPLIMU,Nominalwherein, VPLGNSS,faultVPL, a vertical protection level under the assumption of global satellite navigation system failureIMU,faultFor the vertical protection level under the assumption of inertial navigation faults, VPLIMU,NominalIs the vertical protection level under the nominal assumption of inertial navigation.
According to the embodiment of the invention, the vertical protection level VPL under the nominal assumption of inertial navigationIMU,NominalCalculated by the following method:
VPLIMU,Nominal＝Kmd,INS,VσIMU,std,v，
wherein σIMU,std,vFor the standard deviation of the performance parameter of the inertial measurement unit in the vertical direction, Kmd,INS,VAnd a missing detection coefficient in the vertical direction is assumed for the inertial navigation nominal.
Vertical direction missing detection coefficient K under inertial navigation nominal assumptionmd,INS,VObtained by the following method:
Kmd,INS,V＝Q-1(1-λIMU,std,vPHMI,V,Nominal)，
wherein Q is a cumulative distribution function of zero-mean Gaussian distribution, λIMU,std,vThe weight ratio of integrity risk errors in the vertical direction under the nominal assumption of inertial navigation satisfies 0 < lambdaIMU,std,v＜1，PHMI,V,NominalThe assigned integrity risk in the down-direction is nominally assumed for inertial navigation.
The standard deviation of the performance parameter of the inertial measurement unit in the vertical direction only takes into account the standard deviation in the sky direction, in particular the standard deviation σ of the performance parameter of the inertial measurement unit in the vertical directionIMU,std,vObtained by the following method:
σIMU,std,v＝σIMU,std,U，
wherein σIMU,std,vIs the standard deviation of the north east sky coordinate system. The standard deviation in the north east sky coordinate system is provided by the zero offset values of the different levels of inertial measurement units in table 1.
According to the actual situation of the deviation of the inertial measurement device, the standard deviation in the vertical direction is described only through the standard deviation in the vertical direction, and the integrity in the horizontal direction is guaranteed from the original parameters of inertial navigation.
According to the embodiment of the invention, under the condition that the inertial measurement unit introduces a fault hypothesis, the arithmetic mean of a filter gain term and a process noise deviation correction quantity in an extended Kalman filter state equation is introduced to calculate the HPL under the condition that the inertial navigation fault hypothesis is generatedIMU,fault。
Vertical protection level VPL under specific address and inertial navigation fault assumptionIMU,faultCalculated by the following method:
Figure BDA0002008383790000131
wherein σIMU,fault,vFor fault deviations in the vertical direction under the assumption of inertial navigation faults, Kmd,INS-fault,VSetting a vertical missing detection coefficient for inertial navigation fault, Kk,iIs the kalman filter gain at the current sampling instant i,
Figure BDA0002008383790000132
is the process noise offset correction at the current sampling instant i,ω,ithe noise covariance matrix input for the current time instant i,
Figure BDA0002008383790000133
and k is the state of the extended kalman filter equation in the integrated navigation, and N is 1, 2, …, which is the process noise vector at the current time i.
Under the assumption of inertial navigation faultMissing detection coefficient K in vertical directionmd,INS-fault,VObtained by the following method:
Kmd,INS-fault,V＝Q-1(1-λIMU,fault,vPHMI,V,INS)，
wherein Q is a cumulative distribution function of zero-mean Gaussian distribution, λIMU,fault,vThe weight ratio of integrity risk errors in the vertical direction is assumed for inertial navigation faults and satisfies the condition that lambda is more than 0IMU,fault,v＜1，PHMI,V,INSThe assigned integrity risk in the down-vertical direction is assumed for inertial navigation faults.
Fault deviation σ in vertical direction under inertial navigation fault assumption in case of inertial measurement device introducing fault assumptionIMU,fault,vThe fault deviation of the inertial measurement unit in the north-east direction is determined by the fault deviation of the inertial measurement unit in the north-east direction.
According to an embodiment of the invention, the fault deviation σ in the vertical direction under the assumption of inertial navigation faultIMU,fault,vObtained by the following method:
σIMU,fault,v＝σIMU,fault,U，
wherein σIMU,fault,UThe north east sky coordinate system is the sky fault deviation. According to the sky-direction fault deviation sigma under the northeast sky coordinate systemIMU,fault,UFrom the residual error in the above extended Kalman Filter State equation
Figure BDA0002008383790000141
The standard deviation in the direction of the day is quantified.
According to the embodiment of the invention, the VPL under the fault assumption of the global satellite navigation systemGNSS,faultCalculated by the following method:
Figure BDA0002008383790000142
wherein,
Figure BDA0002008383790000143
is the mean position deviation muk,iComponent μ in the vertical directionk,v,iThe arithmetic mean correction amount of (1), Kffmd,VA vertical missing detection coefficient is assumed for the global navigation system fault,
Figure BDA0002008383790000144
fault deviation in vertical direction under the assumption of global navigation system fault.
In the above process, the average position deviation mu is obtained by using a Receiver Autonomous Integrity Monitoring (RAIM) methodk,iComponent μ in the vertical directionk,v,iThe arithmetic mean correction amount of (1). Obtaining fault deviation in vertical direction under global navigation system fault assumption through extended Kalman filter state Equation (EKF)
Figure BDA0002008383790000145
Missing detection coefficient K in horizontal direction under fault assumption of global navigation systemffmd,VObtained by the following method:
Kffmd,V＝Q-1(1-PHMI,V,GNSS/2)，
wherein Q is a cumulative distribution function of zero-mean Gaussian distribution, PHMI,V,GNSSGlobal navigation system failures assume integrity risks assigned in the vertical direction.
Through the above calculation, a horizontal protection stage (HPL) and a vertical protection stage (VPL) are obtained. The unmanned aerial vehicle is monitored by setting a horizontal warning limit (HAL) and a vertical warning limit (VAL).
According to the invention, the processor further executes the following instructions: and setting a horizontal warning limit by taking the transverse size of the unmanned aerial vehicle as a reference, setting a vertical warning limit by taking the longitudinal size of the unmanned aerial vehicle as a reference, comparing the calculated horizontal protection level of the combined navigation with the horizontal warning limit, and comparing the calculated vertical protection level of the combined navigation with the vertical warning limit to monitor the unmanned aerial vehicle.
In one embodiment, the drone is routed by setting a horizontal warning limit (HAL) and a vertical warning limit (VAL).
Fig. 4 is a schematic diagram illustrating an unmanned aerial vehicle navigation route planning according to an embodiment of the present invention, in which 1.1 to 1.3 times of a transverse dimension of the unmanned aerial vehicle is set as a first horizontal warning limit, and 1.1 to 1.3 times of a longitudinal dimension of the unmanned aerial vehicle is set as a first vertical warning limit, so that a space cube surrounded by the first horizontal warning limit and the first vertical warning limit is reduced to a flight trajectory 300 of the unmanned aerial vehicle 100.
Comparing the calculated horizontal protection level of the integrated navigation with the first horizontal warning limit, comparing the vertical protection level of the integrated navigation with the first vertical warning limit,
when the horizontal protection level is higher than the first horizontal warning limit and/or the vertical protection level is higher than the first vertical warning limit, the horizontal protection level of the combined navigation and the vertical protection level of the combined navigation are recalculated so that the horizontal protection level is lower than the first horizontal warning limit and the vertical protection level is lower than the first vertical warning limit.
In other embodiments, the drone is airspace governed by setting a horizontal warning limit (HAL) and a vertical warning limit (VAL).
Fig. 5 is a schematic view of a boundary of a controlled airspace of an unmanned aerial vehicle according to another embodiment of the present invention, in which 100 to 1000 times of a horizontal size of the unmanned aerial vehicle is set as a second horizontal warning limit, and 100 to 1000 times of a longitudinal size of the unmanned aerial vehicle is set as a second vertical warning limit, so that a space cube surrounded by the second horizontal warning limit and the second vertical warning limit forms the controlled airspace 400 of the unmanned aerial vehicle 100, and the unmanned aerial vehicle 100 flies within the boundary 401 of the controlled airspace 400.
Comparing the calculated horizontal protection level of the integrated navigation with a second horizontal warning limit, comparing the vertical protection level of the integrated navigation with a second vertical warning limit,
when the horizontal protection level is higher than the second horizontal warning limit and/or the vertical protection level is higher than the second vertical warning limit, the horizontal protection level of the combined navigation and the vertical protection level of the combined navigation are recalculated so that the horizontal protection level is lower than the second horizontal warning limit and the vertical protection level is lower than the second vertical warning limit.
According to the integrated navigation integrity monitoring system for the unmanned aerial vehicle, integrity risks are distributed in the horizontal direction and the vertical direction, the integrity risks in the horizontal direction and the vertical direction are divided into a nominal hypothesis, an inertial navigation fault hypothesis and a global navigation fault hypothesis, horizontal protection and vertical protection levels are calculated respectively, the inertial navigation system is realized without hardware redundancy, and the integrated navigation integrity monitoring cost can be reduced.
According to the integrated navigation integrity monitoring system for the unmanned aerial vehicle, hardware redundancy of an Inertial Navigation System (INS) is not needed, so that the navigation cost of the unmanned aerial vehicle is greatly reduced, and interference of redundant information is avoided.
According to the integrated navigation integrity monitoring system for the unmanned aerial vehicle, risks are distributed to a horizontal domain and a vertical domain through integrity risk distribution, and then fault hypotheses of the horizontal domain and the vertical domain are divided into a nominal hypothesis, a global navigation system fault hypothesis and an inertial navigation fault hypothesis, so that the integrity of the system is guaranteed from a system level, and the integrity of each branch is guaranteed from a hardware level.
Aiming at the inertial navigation fault hypothesis, except for setting the error weight ratio, the combined navigation integrity monitoring system for the unmanned aerial vehicle utilizes different miss detection coefficient calculation methods to separate the conditions in the horizontal direction and the vertical direction, can more accurately describe the error deviation conditions in the horizontal direction and the vertical direction in navigation, simultaneously considers the influence of the filter gain and the process noise error of an extended Kalman filter state Equation (EKF) of the combined navigation, and reflects the influence of the algorithm and the actual operation noise on the protection level calculation.
The invention relates to a combined navigation integrity monitoring system for an unmanned aerial vehicle, which adjusts a corresponding calculation method of a missed detection coefficient according to the difference of the resolutions of error deviation generated by satellite faults in the horizontal direction and the vertical direction aiming at the fault assumption of a global navigation system, so that the algorithm corresponding to a horizontal protection level and a vertical protection level can better adapt to the actual error deviation condition.
According to the integrated navigation integrity monitoring system for the unmanned aerial vehicle, planning and tracking of the unmanned aerial vehicle navigation path can be realized only by limiting the horizontal warning limit and the vertical warning limit according to the requirements of practical application. And corresponding horizontal warning limits and vertical warning limits can be set according to the determined specific flight airspace boundary, so that the safe flight of the unmanned aerial vehicle in the control airspace can be realized, and the practical application of corresponding airspace flight prohibition and the like can be derived.
Other embodiments of the invention will be apparent to those skilled in the art from consideration of the specification and practice of the invention disclosed herein. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the invention being indicated by the following claims.

Claims (9)

1. An integrated navigation integrity monitoring system for a drone, the system comprising:
the inertia measurement device is used for providing zero offset values of the inertia measurement devices of different grades for the processor;
a receiver for receiving global satellite navigation signals and providing integrity risks of a global satellite navigation system to a processor;
a processor for calculating a horizontal protection level of the integrated navigation and a vertical protection level of the integrated navigation, wherein the horizontal protection level of the integrated navigation is calculated by the following method:
HPL＝max{HPLGNSS,fault,HPLIMU,fault,HPLIMU,Nominalin which, HPLGNSS,faultFor the level of protection under the assumption of global satellite navigation system failure, HPLIMU,faultFor the level of protection under the assumption of inertial navigation faults, HPLIMU,NominalA horizontal protection level under the nominal assumption of inertial navigation;
the vertical protection level of the combined navigation is calculated by the following method:
VPL＝max{VPLGNSS,fault,VPLIMU,fault,VPLIMU,Nominalwherein, VPLGNSS,faultVPL, a vertical protection level under the assumption of global satellite navigation system failureIMU,faultFor the vertical protection level under the assumption of inertial navigation faults, VPLIMU,NominalThe vertical protection level under the nominal assumption of inertial navigation;
the processor further executes the following instructions: and setting a horizontal warning limit by taking the transverse size of the unmanned aerial vehicle as a reference, setting a vertical warning limit by taking the longitudinal size of the unmanned aerial vehicle as a reference, comparing the calculated horizontal protection level of the combined navigation with the horizontal warning limit, comparing the calculated vertical protection level of the combined navigation with the vertical warning limit, and monitoring the integrity of the unmanned aerial vehicle.
2. The system of claim 1, wherein the inertial navigation nominal assumed horizontal protection level HPLIMU,NominalCalculated by the following method:
HPLIMU,Nominal＝Kmd,INS,HσIMU,std,h，
wherein σIMU,std,hFor the standard deviation of the performance parameter of the inertial measurement unit in the horizontal direction, Kmd,INS,HSetting a missing detection coefficient in the horizontal direction for the inertial navigation nominal value;
missing detection coefficient K in horizontal direction under nominal assumption of inertial navigationmd,INS,HObtained by the following method:
Kmd,INS,H＝Q-1(λIMU,std,hPHMI,H,Nominal)，
wherein Q is a cumulative distribution function of zero-mean Gaussian distribution, λIMU,std,hThe weight ratio of the integrity risk errors in the horizontal direction under the nominal assumption of inertial navigation satisfies 0 & ltlambdaIMU,std,h＜1，PHMI,H,NominalNominally assuming an assigned integrity risk in the horizontal direction for inertial navigation;
standard deviation sigma of performance parameter of the inertia measurement device in horizontal directionIMU,std,hObtained by the following method:
Figure FDA0002673350340000021
wherein σIMU,std,NSit in the north eastStandard deviation of north orientation, σIMU,std,EIs the east standard deviation in the northeast coordinate system.
3. The system of claim 1, wherein the HPL level of protection under inertial navigation fault assumptionIMU,faultCalculated by the following method:
Figure FDA0002673350340000022
wherein σIMU,fault,hFor fault deviations in the horizontal direction under the assumption of inertial navigation faults, Kmd,INS-fault,HSetting a missing detection coefficient in the horizontal direction for inertial navigation fault, Kk,iIs the kalman filter gain at the current sampling instant i,
Figure FDA0002673350340000023
is the process noise offset correction at the current sampling instant i,ω,ithe noise covariance matrix input for the current time instant i,
Figure FDA0002673350340000024
k is a process noise vector of the current time i, the state of an extended Kalman filtering equation in the integrated navigation is k, and N is 1, 2 and …;
missing detection coefficient K in horizontal direction under inertial navigation fault assumptionmd,INS-fault,HObtained by the following method:
Kmd,INS-fault,H＝Q-1(λIMU,fault,hPHMI,H,INS)，
wherein Q is a cumulative distribution function of zero-mean Gaussian distribution, λIMU,fault,hThe weight ratio of integrity risk errors in the horizontal direction is assumed for inertial navigation faults and satisfies the condition that lambda is more than 0IMU,fault,h＜1，PHMI,H,INSAssuming an integrity risk assigned in the horizontal direction for inertial navigation faults;
horizontal fault deviation under inertial navigation fault assumptionDifference sigmaIMU,fault,hObtained by the following method:
Figure FDA0002673350340000025
wherein σIMU,fault,NIs the deviation of north fault in the coordinate system of northeastIMU,fault,EIs the east fault deviation in the northeast coordinate system.
4. The system of claim 1, wherein the HPL is a level protection level under the assumption of a global satellite navigation system failureGNSS,faultCalculated by the following method:
Figure FDA0002673350340000031
wherein,
Figure FDA0002673350340000032
is the mean position deviation muk,iComponent μ in the horizontal directionk,h,iThe arithmetic mean correction amount of (1), Kffmd,HA missing detection coefficient in the horizontal direction is assumed for the fault of the global satellite navigation system,
Figure FDA0002673350340000033
for a fault deviation in the horizontal direction under the assumption of a global satellite navigation system fault,
missing detection coefficient K in horizontal direction under fault assumption of global satellite navigation systemffmd,HObtained by the following method:
Kffmd,H＝Q-1(PHMI,H,GNSS/2)，
wherein Q is a cumulative distribution function of zero-mean Gaussian distribution, PHMI,H,GNSSAn assigned integrity risk in the horizontal direction is assumed for global satellite navigation system failures.
5. According toThe system of claim 1, wherein the vertical protection stage VPL under the nominal assumption of inertial navigationIMU,NominalThe inertial navigation is calculated under the nominal assumption by the following method:
VPLIMU,Nominal＝Kmd,INS,VσIMU,std,v，
wherein σIMU,std,vFor the standard deviation of the performance parameter of the inertial measurement unit in the vertical direction, Kmd,INS,VSetting a missing detection coefficient in the vertical direction for the inertial navigation nominal hypothesis;
the missing detection coefficient K in the vertical direction under the nominal assumption of inertial navigationmd,INS,VObtained by the following method:
Kmd,INS,V＝Q-1(1-λIMU,std,vPHMI,V,Nominal)，
wherein Q is a cumulative distribution function of zero-mean Gaussian distribution, λIMU,std,vThe weight ratio of integrity risk errors in the vertical direction under the nominal assumption of inertial navigation satisfies 0 < lambdaIMU,std,v＜1，PHMI,V,NominalNominally assuming an assigned integrity risk in the down-vertical direction for inertial navigation;
the standard deviation sigma of the performance parameter of the inertial measurement unit in the vertical directionIMU,std,vObtained by the following method:
σIMU,std,v＝σIMU,std,U，
wherein σIMU,std,vIs the standard deviation of the north east sky coordinate system.
6. System according to claim 1, characterized in that the vertical protection level VPL under inertial navigation fault assumptionIMU,faultCalculated by the following method:
Figure FDA0002673350340000034
wherein σIMU,fault,vFor fault deviations in the vertical direction under the assumption of inertial navigation faults, Kmd,INS-fault,VSetting a vertical missing detection coefficient for inertial navigation fault, Kk,iIs the kalman filter gain at the current sampling instant i,
Figure FDA0002673350340000041
is the process noise offset correction at the current sampling instant i,ω,ithe noise covariance matrix input for the current time instant i,
Figure FDA0002673350340000042
k is a process noise vector of the current time i, the state of an extended Kalman filtering equation in the integrated navigation is k, and N is 1, 2 and …;
vertical direction missing detection coefficient K under inertial navigation fault assumptionmd,INS-fault,VObtained by the following method:
Kmd,INS-fault,V＝Q-1(1-λIMU,fault,vPHMI,V,INS)，
wherein Q is a cumulative distribution function of zero-mean Gaussian distribution, λIMU,fault,vThe weight ratio of integrity risk errors in the vertical direction is assumed for inertial navigation faults and satisfies the condition that lambda is more than 0IMU,fault,v＜1，PHMI,V,INSAssuming an assigned integrity risk in the vertical direction for inertial navigation faults;
fault deviation σ in vertical direction under assumption of inertial navigation faultIMU,fault,vObtained by the following method:
σIMU,fault,v＝σIMU,fault,U，
wherein σIMU,fault,UThe north east sky coordinate system is the sky fault deviation.
7. The system according to claim 1, wherein the VPL is a vertical protection level under the assumption of global satellite navigation system failureGNSS,faultCalculated by the following method:
Figure FDA0002673350340000043
wherein,
Figure FDA0002673350340000044
is the mean position deviation muk,iComponent μ in the vertical directionk,v,iThe arithmetic mean correction amount of (1), Kffmd,VA vertical missing detection coefficient is assumed for the global satellite navigation system fault,
Figure FDA0002673350340000045
for a fault deviation in the vertical direction under the assumption of a global satellite navigation system fault,
missing detection coefficient K in horizontal direction under fault assumption of global navigation systemffmd,VObtained by the following method:
Kffmd,V＝Q-1(1-PHMI,V,GNSS/2)，
wherein Q is a cumulative distribution function of zero-mean Gaussian distribution, PHMI,V,GNSSThe assigned integrity risk in the down-vertical direction is assumed for gnss faults.
8. The system of claim 1, wherein 1.1-1.3 times of the transverse dimension of the unmanned aerial vehicle is set as a first horizontal warning limit, 1.1-1.3 times of the longitudinal dimension of the unmanned aerial vehicle is set as a first vertical warning limit, the space cube enclosed by the first horizontal warning limit and the first vertical warning limit is reduced to the flight trajectory of the unmanned aerial vehicle,
comparing the calculated horizontal protection level of the integrated navigation with the first horizontal warning limit, comparing the vertical protection level of the integrated navigation with the first vertical warning limit,
when the horizontal protection level is above the first horizontal warning limit and/or the vertical protection level is above the first vertical warning limit, the horizontal protection level of the combined navigation and the vertical protection level of the combined navigation are recalculated so that the horizontal protection level is below the first horizontal warning limit and the vertical protection level is below the first vertical warning limit.
9. The system of claim 1, wherein 100-1000 times of the transverse dimension of the unmanned aerial vehicle is set as a second horizontal warning limit, 100-1000 times of the longitudinal dimension of the unmanned aerial vehicle is set as a second vertical warning limit, and a space cube enclosed by the second horizontal warning limit and the second vertical warning limit forms a flight space of the unmanned aerial vehicle,
comparing the calculated horizontal protection level of the integrated navigation with a second horizontal warning limit, comparing the vertical protection level of the integrated navigation with a second vertical warning limit,
when the horizontal protection level is higher than the second horizontal warning limit and/or the vertical protection level is higher than the second vertical warning limit, the horizontal protection level of the combined navigation and the vertical protection level of the combined navigation are recalculated so that the horizontal protection level is lower than the second horizontal warning limit and the vertical protection level is lower than the second vertical warning limit.
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